{"id":221884,"date":"2025-09-15T00:04:05","date_gmt":"2025-09-15T05:04:05","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2025\/09\/machine-learning-for-materials-discovery-and-optimization"},"modified":"2025-09-15T00:04:05","modified_gmt":"2025-09-15T05:04:05","slug":"machine-learning-for-materials-discovery-and-optimization","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2025\/09\/machine-learning-for-materials-discovery-and-optimization","title":{"rendered":"Machine learning for materials discovery and optimization"},"content":{"rendered":"<p style=\"padding-right: 20px\"><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/machine-learning-for-materials-discovery-and-optimization.jpg\"><\/a><\/p>\n<p><strong>This Collection supports and amplifies research related to <a href=\"https:\/\/sdgs.un.org\/goals\/goal9\">SDG 9 \u2014 Industry, Innovation &amp; Infrastructure<\/a>.<\/strong><\/p>\n<p>Discovering new materials with customizable and optimized properties, driven either by specific application needs or by fundamental scientific interest, is a primary goal of materials science. Conventionally, the search for new materials is a lengthy and expensive manual process, frequently based on trial and error, requiring the synthesis and characterization of many compositions before a desired material can be found. In recent years this process has been greatly improved by a combination of artificial intelligence and high-throughput approaches. Advances in machine learning for materials science, data-driven materials prediction, autonomous synthesis and characterization, and data-guided high-throughput exploration, can now significantly accelerate materials discovery.<\/p>\n<p>This Collection brings together the latest computational and experimental advances in artificial intelligence, machine learning and data-driven approaches to accelerate high-throughput prediction, synthesis, characterization, optimization, discovery, and understanding of new materials.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This Collection supports and amplifies research related to SDG 9 \u2014 Industry, Innovation &amp; Infrastructure. Discovering new materials with customizable and optimized properties, driven either by specific application needs or by fundamental scientific interest, is a primary goal of materials science. Conventionally, the search for new materials is a lengthy and expensive manual process, frequently [\u2026]<\/p>\n","protected":false},"author":732,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1635,6],"tags":[],"class_list":["post-221884","post","type-post","status-publish","format-standard","hentry","category-materials","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/221884","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/732"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=221884"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/221884\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=221884"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=221884"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=221884"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}